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08417 A Verified Computer Model for Corrosion Rate Prediction in a Di-ethanol Amine System Using Field Data

Picture for 08417 A Verified Computer Model for Corrosion Rate Prediction in a Di-ethanol Amine System Using Fie
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Product Number: 51300-08417-SG
ISBN: 08417 2008 CP
Author: Mahdi Nouri, Jafar Mesbah, and Soheil Shaibani
Publication Date: 2008
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Many parameters affect corrosion rate significantly such as operating temperature, CO2 and H2S partial pressure, CO2 and H2S ratio, type of process fluid, dissolved chlorides, pH, operating conditions, scaling tendency of corrosion products, oil wetting, type of corrosion inhibitor used and its efficiency, flow velocity of gas phase and/or multiphase systems, and material of construction. The purpose of this paper is to demonstrate the effect of the parameters and application of methods predicting corrosion rate in gas treating plants using DEA (Di-Ethanol Amine) aqueous solution. A computer model is developed to predict the corrosion rate at gas processing units considering the effects of the above parameters and amine type in a semi-empirical model. The model is verified by comparing predicted corrosion rates based upon selected material of construction with measured corrosion rates data obtained from the field and the design life expectancy of the plant.
Many parameters affect corrosion rate significantly such as operating temperature, CO2 and H2S partial pressure, CO2 and H2S ratio, type of process fluid, dissolved chlorides, pH, operating conditions, scaling tendency of corrosion products, oil wetting, type of corrosion inhibitor used and its efficiency, flow velocity of gas phase and/or multiphase systems, and material of construction. The purpose of this paper is to demonstrate the effect of the parameters and application of methods predicting corrosion rate in gas treating plants using DEA (Di-Ethanol Amine) aqueous solution. A computer model is developed to predict the corrosion rate at gas processing units considering the effects of the above parameters and amine type in a semi-empirical model. The model is verified by comparing predicted corrosion rates based upon selected material of construction with measured corrosion rates data obtained from the field and the design life expectancy of the plant.
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